Antoniou C.,National Technical University of Athens |
Barcelo J.,University of Barcelona |
Breen M.,TSS Transport Simulation Systems |
Bullejos M.,University of Barcelona |
And 12 more authors.
Transportation Research Part C: Emerging Technologies | Year: 2015
Estimation/updating of Origin-Destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in on-line contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks - except from closed highway systems - thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under "standardized" conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources. © 2015 Elsevier Ltd.
Ciuffo B.,Institute for the Environment and Sustainability |
Casas J.,TSS Transport Simulation Systems |
Montanino M.,University of Naples Federico II |
Perarnau J.,TSS Transport Simulation Systems |
Punzo V.,European Commission - Joint Research Center Ispra
Transportation Research Record | Year: 2013
This study adopted a metamodel-based technique for model sensitivity analysis and applied it to the AIMSUN mesoscopic model. The application of sensitivity analysis is crucial for the true comprehension and correct use of the traffic simulation model, although the main obstacle to an extensive use of the most sophisticated techniques is the high number of model runs such techniques usually require. For this reason, the possibility of performing a sensitivity analysis was tested not on a model but on its metamodel approximation. Important issues concerning metamodel estimation were investigated and commented on in the specific application to the AIMSUN model. Among these issues are the importance of selecting a proper sampling strategy based on low-discrepancy random number sequences and the importance of selecting a class of metamodels able to reproduce the inputs-outputs relationship in a robust and reliable way. Sobol sequences and Gaussian process metamodels were recognized as the appropriate choices. The proposed methodology was assessed by comparing the results of the application of variance-based sensitivity analysis techniques with the simulation model and with a metamodel estimated with 512 model runs for a variety of traffic scenarios and model outputs. Results confirmed the power of the proposed methodology and also made a more extensive application of sensitivity analysis techniques available for complex traffic simulation models.
Vilaro J.C.,TSS Transport Simulation Systems |
Vilaro J.C.,University of Vic |
Torday A.,TSS Transport Simulation Systems |
Gerodimos A.,TSS Transport Simulation Systems
IEEE Intelligent Transportation Systems Magazine | Year: 2010
The evaluation of advanced Intelligent Transportation Systems, and particularly those which involve real-time traffic management, requires a network-wide assessment of their impact as opposed to an isolated analysis of key intersections. To support such assessments, an integrated simulation environment that allows the use of different modeling levels (e.g., macro-meso-micro) offers undeniable advantages. One of the advantages is that traffic assignment results produced by any type of network loading modeling can be stored and reused for another simulation run. But even in an integrated environment with separate models, deciding between microscopic or mesoscopic was until recently a necessary and difficult choice. On the one hand, microscopic traffic simulation models emulate the dynamics of individual vehicles in a detailed network representation based on car-following, lane changing, and gap acceptance models. They also account explicitly for traffic control. As such, they are very appropriate for operational analysis due to the detail of information provided by the simulator. However, they have a significant calibration and computational cost. On the other hand, mesoscopic models combine simplified flow dynamics with explicit treatment of interrupted flows at intersections and allow modeling of large networks with high computational efficiency. However, the loss of realism implied by a mesoscopic model makes it necessary to emulate detailed outputs; for instance, de-tector measurements or instantaneous emissions. Some outputs, such as the number of start-stops or the exact location of con-gestion within a section elude even the most detailed mesoscopic simulators. This analysis gives rise to the need to combine meso and micro approaches into new concurrent hybrid traffic simulators where very large-scale networks are modeled mesoscopically and areas of complex interactions benefit from the finer detail of microscopic simulation. Combining an event-based mesoscopic model with a more detailed, time-sliced microsimulator raises consistency problems within the network rep-resentation and the meso-micro-meso transitions. This paper discusses these problems, proposes solutions and illustrates how they work in practice. © 2010 IEEE.
Tss Transport Simulation; Systems | Date: 2010-01-12
Computer programs for analyzing and simulating mobility of people and goods and multi-modal surface traffic, namely, private vehicles, public transport, logistics fleet vehicles, emergency vehicles, motorcycles as well as pedestrians, bicycles and other non motorized vehicles.